Impact Evaluation in Firms and Organizations (Record no. 66632)

MARC details
000 -LEADER
fixed length control field 02351nam a22002177a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251124100006.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 251124b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780262552929
028 ## - DISTRIBUTOR NAME
Distributor Name : Samyak Publisher
Distributor address : Ghaziabad
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 658.4 HUB
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Huber, Martin.
245 ## - TITLE STATEMENT
Title Impact Evaluation in Firms and Organizations
Remainder of title : With Applications in R and Python.
Statement of responsibility, etc / Martin Huber.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc , London
Name of publisher, distributor, etc : The MIT Press
Date of publication, distribution, etc , 2025.
300 ## - PHYSICAL DESCRIPTION
Extent vii, 144p.
Dimensions : 24cm.
520 ## - SUMMARY, ETC.
Summary, etc A comprehensive, nontechnical guide to the methods of data-based impact evaluation in companies and organizations, with coverage of machine learning techniques.<br/><br/>In today's dynamic business climate, organizations face the constant challenge of making informed decisions about their interventions, from marketing campaigns and pricing strategies to employee training programs. In this practical textbook, Martin Huber provides a concise but comprehensive guide to quantitatively assessing the impact of such efforts, enabling decision-makers to make evidence-based choices.<br/><br/>The book introduces fundamental concepts, emphasizing the importance of causal analysis in understanding the true effects of interventions, before detailing a wide range of quantitative methods, including experimental and nonexperimental approaches. Huber then explores the integration of machine learning techniques for impact evaluation in the context of big data, sharing cutting-edge tools for data analysis. Centering real-world, global applications, this accessible text is an invaluable resource for anyone seeking to enhance their decision-making processes through data-driven insights.<br/><br/>Highlights the relevance of AI and equips readers to leverage advanced analytical techniques in the era of digital transformation<br/>Is ideal for introductory courses on impact evaluation or causal analysis<br/>Covers A/B testing, selection-on-observables, instrumental variables, regression discontinuity designs, and difference-in-differences<br/>Features extensive examples and demonstrations in R and Python<br/>Suits a wide audience, including business professionals and students with limited statistical expertise
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Impact Evaluation
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Applications in R and Python
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning techniques
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Martin Huber.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Full call number Barcode Checked out Date last seen Date checked out Price effective from Koha item type
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 24/11/2025 Samyak Vidyasagar 1 658.4 HUB 31228 26/12/2025 26/11/2025 26/11/2025 24/11/2025 Books
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